The Centers for Disease Control and Prevention’s
(CDC) significant patronage of U.S. vaccines affords them leverage in
negotiating public-sector prices that prevent the formation of
monopolies. This work
is the first in the literature to incorporate the CDC as a strategic agent in the vaccine pricing market. Our
optimization model from the CDC’s perspective captures US goals, links
dynamics in public and private sectors, and incorporates competitive
manufacturer behavior via an embedded Bertrand-Edgeworth-Chamberlin
game. The model is validated in an extended case
study of the diphtheria, tetanus, and acellular pertussis (DTaP)
vaccine and is extended to the U.S. COVID-19 vaccine duopoly that was initially defined
by Pfizer-BioNTech and Moderna through February 2021. The
study indicates that our model can help re-stabilize a market that
experiences a vaccine shortage and that the CDC might mitigate
the same shortage using strategies that depend on which manufacturer is
limited. These results support a paradigm shift from annual pricing
contracts to ongoing negotiations in pediatric vaccine markets, which
would enable the CDC to exercise more granular
control over high-risk markets. Furthermore, the
results suggest that even in the context of very high production and
distribution costs, the CDC can negotiate COVID-19 vaccine prices
with manufacturers to keep public sector
prices as low as possible while meeting CDC goals. We have predicted
optimal COVID-19 vaccine prices that were consistent with those that
were anticipated by the media at the time of writing.
This work is joint with Susan Martonosi and Banafsheh Behzad.
Bio:
Kayla
Cummings is a PhD candidate in Operations Research at the Massachusetts
Institute of Technology, advised by Alexandre Jacquillat and Vikrant
Vaze. In her graduate work, she develops decomposition methods
for large-scale optimization models toward integrated and optimal
design of urban transportation systems. She has conducted research in
cybersecurity, computational mathematics, operations research, graph
theory, and algorithmic algebraic geometry at Oak Ridge
National Laboratory, DIMACS at Rutgers University, Harvey Mudd
College, Pomona College, and Texas A&M University. Kayla
is a recipient of the MIT Teaching + Learning Lab's Teaching
Development Fellowship, the NSF Graduate Research Fellowship, and the
2018
INFORMS Undergraduate Research Prize. She graduated magna cum laude with a B.A. in Mathematics from Pomona College. In her spare time,
Kayla loves indoor rock climbing, distance
running, classical piano, reading, petting every dog she encounters, and
consuming expensive coffee.